Academic Journal of Science and Technology ISSN: 2771-3032 | Vol. 10, No. 1, 2024 278 Employment Policy, Employment Capital, and Employment Intention of Guangdong Private College Students Shengping Lin1, *, Cheng-jui Tseng1, a 1Rattanakosin International College of Creative Entrepreneurship, Rajamangala University of Technology Rattanakosin, Nakhon Pathom 73170, Thailand *Corresponding author Email: 1156788374@qq.com, a1652110471101@rmutr.ac.th Abstract: The purpose of this study is to explore the employment intention of private college students in Guangdong, and to analyze the relationship between employment policy, employment capital and employment intention, in order to promote the employment and economic development in Guangdong. The study adopted a quantitative approach, using an online questionnaire to survey 612 students, using a variety of data analysis tools to ensure research rigor. It is found that attitude has a significant impact on employment policy and subjective norms on employment capital and employment intention, and employment capital plays an intermediary role in the relationship between these two pairs. The findings deepen our understanding of how individual attitudes, social norms, and employment capital work together to shape employment intentions, highlight the importance of cultivating positive employment attitudes and supportive social norms to enhance employment capital, and provide targeted interventions and policy recommendations for education and employment stakeholders to improve employment outcomes. Keywords: Employment Intentions; Structural Equation Modeling; Attitude to Employment Policies; Subjective Norm; Employment Capital. 1. Introduction The research presented in this chapter focuses on the interplay between employment policy, employment capital, and employment intention among students at Guangdong private colleges and universities. This study is situated within the broader context of China's rapidly developing economy and the specific challenges faced by the employment market in Guangdong Province, a key economic hub. China has long been committed to addressing employment issues, implementing various policies aimed at fostering graduate employability, including those related to vocational education and entrepreneurship. Guangdong Province, with its vibrant economy and developed employment market, has been at the forefront of these efforts, issuing multiple policy documents to encourage innovation, entrepreneurship, and private enterprise development among college students. These policies reflect a dual aim: enhancing students' employability and contributing to the province's economic growth. Despite these initiatives, Guangdong faces employment market challenges such as structural imbalances and skills mismatches. The province's rapid economic development has coincided with increased college graduation rates, intensifying job market competition. Moreover, contemporary youth exhibit a stronger preference for career development opportunities and personal fulfillment over mere financial gain, influencing their employment choices. Guangdong's private higher education sector has grown significantly, with numerous private universities contributing to the region's educational landscape. As of 2021, there were 65 private colleges and universities in Guangdong, including 36 private undergraduate institutions and 29 private junior colleges. However, despite this expansion, graduates from these institutions continue to face employment difficulties. The objective of this research is to examine the impact of Guangdong's employment policies on employment capital and how these factors influence the employment intentions of students at private colleges and universities. By analyzing policy documents, academic literature, and empirical data, the study aims to identify gaps and suggest strategies to improve the alignment between policy objectives, educational resources, and graduate aspirations, thereby enhancing overall employment outcomes in the region. The findings will contribute to a better understanding of the dynamics shaping graduate employment in Guangdong and inform policy recommendations to address existing challenges. 2. Problems Faced by College Students in Employment Graduates' employment policy, employment capital and employment intention are the key issues of Guangdong private university students. With the advancement of science and technology and digital transformation, traditional industries are undergoing changes, and new industries and occupations are constantly emerging. This is both an opportunity and a challenge for young people. Technological progress and changes in industrial structure have led to a decrease in employment opportunities in some traditional industries, while employment opportunities in emerging industries and technology fields have gradually increased. However, some private higher education institutions in Guangdong may not be able to keep up with the pace of technological development, resulting in a mismatch between graduates' skills and market demand, increasing the difficulty of employment. The failure of curricula and teaching methods to meet the needs of the job market will exacerbate the problem. The rise of AI technology may have an impact on certain traditional occupations, thereby reducing employment 279 opportunities for graduates. Guangdong's private college graduates are relatively concentrated in traditional career fields, which may be affected by AI technology. In addition, students lack practical experience and practical skills training opportunities during their studies, resulting in insufficient skill matching and lack of experience after graduation, further increasing the difficulty of employment. Therefore, the development of technology has brought challenges to the students of private universities in Guangdong. In order to cope with these problems, these institutions need to pay attention to technological trends and market demands, adjust curricula and teaching methods in a timely manner, and improve the skills and competitiveness of graduates. At the same time, the contact and cooperation with employers should be strengthened to provide more practical opportunities and employment information for graduates. At present, there are 67 undergraduate colleges and universities in Guangdong Province, including 18 private undergraduate colleges and universities, which is the province with the largest number of private undergraduate colleges and universities, and the number of private undergraduate students is relatively high, more than 500,000, ranking first in China. However, compared with public university students, there is a significant gap in the employment rate and employment quality. Therefore, private colleges and universities in Guangdong need to take effective measures to enhance students' job prospects and ensure that they can adapt to the rapidly changing labor market demands. The study dissects key employment quality metrics, such as salary range and job stability, revealing that public university graduates command higher salaries and enjoy greater job security. This could be attributed to the perceived value of their education, the prevalence of certain fields of study, and enhanced networking opportunities afforded by public institutions. Job satisfaction also varies, with public university graduates exhibiting a higher degree of contentment with their employment situations. These findings underscore the critical need to investigate underlying reasons for these disparities and to formulate strategies to improve employment prospects for private university graduates. They also serve as a vital resource for educational stakeholders, prompting them to consider ways to enhance the employment landscape for graduates across all institutions. The research's broader aim is to examine the interplay between employment policies, employment capital, and the employment intentions of students at private colleges in Guangdong, offering policy recommendations to address these issues. By doing so, the study aims to contribute to a deeper understanding of the factors influencing employment decisions and to foster a more conducive environment for graduate employment in Guangdong, ultimately benefiting both students and the regional economy. With a substantial economic output and a robust manufacturing and trade sector, Guangdong offers diverse employment opportunities that significantly impact the career choices of its graduates. The study's findings, based on employment rate comparisons between private and public universities, suggest that while private institutions are showing improvements, they still lag behind their public counterparts. This disparity underscores the need for targeted interventions to enhance the employability of private university students and align their skills with labor market demands. However, the research faces several limitations that warrant attention. Data reliability could be compromised due to the constraints of available sources, necessitating cautious interpretation of results. Additionally, the heterogeneity among students from different institutions, disciplines, and academic years introduces complexity into the sampling process, potentially leading to biased conclusions. The exclusive use of quantitative methods, such as questionnaires, without integrating qualitative approaches like interviews and focus groups limits the depth of insights gained. Furthermore, discerning causality within the interplay of employment policy, capital, and intention is challenging without employing methodologies specifically designed to address this issue. Finally, the ever-evolving nature of the job market means that the study's relevance could diminish with time, necessitating periodic updates to stay abreast of current trends. The Theory of Planned Behavior (TPB) provides a valuable lens for examining the complex interplay of attitudes, subjective norms, and perceived behavioral control that shape the employment intentions of students at private colleges and universities in Guangdong. By delving into these three core constructs, educators and policymakers can gain insights into the motivations and barriers that influence student career choices. Attitudes, which reflect students' overall evaluation of a given occupation or job sector, are pivotal in determining their pursuit of specific career paths. A positive attitude, cultivated through exposure to relevant knowledge and experiences, serves as a strong predictor of employment intentions. For instance, students who perceive a high value in entrepreneurship may be more inclined to start their own businesses upon graduation. Subjective norms, encompassing the social influences exerted by family, friends, and society, also wield significant influence over students' career decisions. The expectations of these important others can either propel students towards certain fields or deter them from paths that are seen as less conventional or lucrative. This highlights the importance of social support systems in fostering a conducive environment for career growth. Perceived behavioral control, which relates to students' confidence in their ability to secure and maintain employment, is intrinsically linked to their self-efficacy and access to resources. Students who feel well-prepared with the necessary skills and equipped with adequate job market information are more likely to exhibit proactive employment behaviors. Conversely, a lack of confidence or insufficient resources can hinder their job search efforts. Moreover, acknowledging gender and cultural differences within the TPB framework is essential. For example, male and female students might differ in their career aspirations due to societal norms and expectations, while cultural values could moderate the impact of attitudes and norms on employment intentions. In the study of employment policy, employment capital, and employment intention among students in Guangdong private colleges and universities, the subjective norm of employment policy emerges as a critical factor. It represents the social expectations and pressures that influence individuals' support for or engagement with specific employment policies. Research in this area connects to broader themes of social influence, policy attitudes, and compliance, providing insights into how social pressures shape policy support and compliance. Employment capital, a multifaceted construct encompassing human capital, social capital, and cultural 280 capital, is pivotal in enhancing employment prospects and career success. Human capital relates to the knowledge and skills acquired through education and experience, influencing labor market outcomes. Social capital involves the networks and relationships that facilitate access to employment-related information and opportunities. Cultural capital, including cultural knowledge and practices, also impacts employability and career trajectory. Employment capital, comprising resources, knowledge, and skills, is pivotal to labor market health, signaling a plethora of job opportunities and motivating individuals to seek employment. It reflects a robust educational and training system, enhancing individuals' confidence in their employability and bolstering their intention to work. Positive employment capital also heralds favorable working conditions, fair labor practices, and a supportive environment, further stimulating job search intentions. Economic stability and employment opportunities underpinned by strong employment capital engender job seeker confidence. Moreover, a well-established network of social and professional connections facilitates job information access, amplifying employment intentions. Employment capital is synonymous with income and career growth prospects, augmenting motivation to engage in the labor market. Labor markets enriched with robust employment capital lure esteemed employers and enhance regional repute, heightening employment intentions when perceived as offering prestige and superior living standards. Consequently, employment capital positively influences employment intentions. Social capital, acting as a mediator, reflects labor market resources and opportunities. A favorable attitude towards employment policies stimulates investment in education and skills development, reinforcing employment capital and rendering the labor market more attractive to job seekers. Effective policies backed by positive attitudes foster job creation and economic growth, augmenting employment intentions. Attitudes conducive to compliance with labor regulations and fair practices stabilize the labor market, enhancing employment capital's allure. Inclusive employment policies that address societal needs bolster social cohesion and diminish income inequalities, nurturing supportive environments that encourage greater labor market participation. A healthy employment capital contributes to a stable economy and creates a sense of security for job seekers. When individuals perceive that the economy is stable and that job opportunities are plentiful, their willingness to find and maintain work may increase. Strong employment capital typically includes well-developed networks of social and professional contacts, and when individuals have access to such networks, they are more likely to receive information about job opportunities and career advancement, thereby increasing their willingness to seek employment. Positive employment capital indicates ample opportunities for income and career growth. When individuals believe they can achieve financial stability and career advancement by participating in the labor market, they are more likely to be motivated to seek and maintain work. Having a strong employment capital in the labor market will attract high-quality employers and enhance the overall reputation of the region or country. A positive employment policy attitude encourages investment in education, training and skills development. Effective employment policies predict the creation of jobs and economic growth. A positive attitude contributes to labor market stability by encouraging compliance with regulations and promoting fair labor practices, which in turn enhances employment capital and makes participation in the labor market more attractive. When employment policies are designed to be inclusive and address the needs of various groups in society, they contribute to social cohesion and reduce income inequality. This positively impacts employment capital, encouraging more people to participate in the Labour market by fostering a stable and supportive social environment. When employment capital mediates the relationship between attitudes and employment intentions, it underscores the need to create a conducive labor market full of opportunity, growth, and success. Moreover, subjective norms are linked to employment policies, leading to greater social support for those policies. Positive objective norms promote adherence to best practices in the labor market, which leads to improved working conditions, increased productivity, and improved labor market efficiency, ultimately enhancing employment capital.See Figure 1. Figure 1. The research conceptual framework 3. Data Collection Design Analysis Utilizing an online questionnaire, the research meticulously captures student perspectives on demographic factors, employment policy attitudes, subjective norms of employment policies, perceptions of employment capital, and 281 employment intentions. The questionnaire, detailed in the appendix, probes into nine aspects of employment policy attitudes, seven aspects of subjective norms, seven topics related to employment capital, and another seven concerning employment intentions. The study's population is specifically drawn from Guangdong's private university students, reflecting a cross- section of the region's higher education landscape. A rigorous multi-stage stratified random sampling method was employed to ensure a representative sample of students across various universities and majors. The target population includes all current students in Guangdong's private universities, with universities categorized into small, medium, and large strata to capture the diversity of institutional environments. Sampling was conducted in a systematic manner, starting with a compilation of a comprehensive list of private universities in Guangdong, including student enrollment figures. Proportionate random selection was then applied within each stratum, ensuring that the sample encompassed a variety of institution sizes. Major fields of study were also stratified to represent the academic diversity influencing employment prospects. The study aimed for an adequate response rate, employing follow-up actions with non-respondents and, if necessary, augmenting the sample size from the exhaustive list of students. This structured sampling approach guarantees a balanced representation of Guangdong's diverse student population, yielding robust and reliable data for the study. In terms of sample size determination, focusing on the top ten private schools, representing 52% of the total student population, the study aims to provide a comprehensive analysis of the employment intentions of these students. Such a targeted sample size calculation is pivotal for the study's credibility and applicability of its findings to the broader student body in Guangdong's private higher education sector.See Table 1. Table 1. Student Population Distribution Across Private Higher Education Institutes in Guangdong. Private higher education institutes in Guangdong Population Baiyun University in Guangdong 22,732 Zhongshan College of Electronic Science and Technology University 30,799 Guangdong Peizheng College 29,845 Guangdong Neusoft University 23,264 Guangzhou City Institute of Technology 33,123 Guangzhou Software College 24,859 Guangzhou Southern College 34,019 South China Business School, Guangdong University of Foreign Studies, and Business 29,225 Guangzhou Huashang University 27,891 Zhanjiang University of Science and Technology 24,373 Source: China University Students Network (2022). To determine the sample size for a survey, the following formula: n = (Z^2 * P * (1-P)) / E^2 Where: n = sample size Z = Z-score (corresponding to the confidence level, typically 1.96, representing a 95% confidence level) P = proportion of the population with a certain characteristic (if unsure, use 0.5) E = margin of error (for example, 0.05 represents a 5% margin of error) After calculating, we will need to make a finite population correction to the result to determine the sample size more accurately. The corrected formula is: n_adjusted = (N * n) / (N + n) Where: n_adjusted = adjusted sample size N = total population (476,063) Assuming we use a 95% confidence level (Z = 1.96), a population proportion of 0.5 (P = 0.5), and a 5% margin of error (E = 0.05), we calculate the sample size. First, calculate n: n = (1.96^2 * 0.5 * (1 - 0.5)) / 0.05^2 n ≈ 384.16 Then make the finite population correction: n_adjusted = (476,063 * 384.16) / (476,063 + 384.16) n_adjusted ≈ 383.49 The adjusted sample size is approximately 383 or 384. This study adopts the method of quota sampling to study the employment policy, employment capital and employment intention of students in private colleges and universities in Guangdong Province, so as to ensure a representative cross- section sample. Larger universities, such as Guangzhou Nanfang University and Guangzhou City Vocational and Technical College, contribute more to the sample due to the larger number of students, while smaller universities, such as Guangdong Baiyun University and Guangdong Neusoft University, provide fewer participants. The strategy aims to reduce sampling bias, improve survey reliability and applicability to the wider student population of the private higher education sector in the region. This is essential to understand the different employment aspirations and trends of students, thereby informing employment policies and improving the utilization of human capital in the context of Guangdong's dynamic labor market.Subjective norms regarding employment policy are measured by a scale that assesses an individual's perception of social pressure from significant sources such as family and colleagues, 282 encouraging compliance with certain work-related practices. Employment capital is determined using a scale that assesses personal resources, including skills, knowledge, and experience, that contribute to success in the job market. Finally, employment intentions are measured using a scale that looks at an individual's desire to find or keep a job in a particular industry or role. By analyzing these variables, this study hopes to uncover the various factors that influence employment-related decisions and attitudes. 4. Model Analysis The relationship between employment policy, employment capital and employment intention of students in Guangdong private colleges and universities is critically investigated. Using a range of statistical methods, including reliability and validity tests, this chapter rigorously analyzes the collected data. It is worth noting that Cronbach's Alpha coefficient was used for reliability analysis, and an unusually high score of 0.945 was obtained, indicating strong internal consistency among the 30 items in the scale. This finding is particularly noteworthy given the complexity of the structures involved and the challenges of achieving such a high level of reliability in social science research. The high Cronbach's Alpha value of the scale and the large number of items both reflect the comprehensive and thorough operability of the structure, providing a solid foundation for the subsequent analysis and interpretation of this study. The KMO measure used in this paper to assess whether the sample was sufficient for factor analysis produced a very high value of 0.964, well above the recommended threshold of 0.6. This indicates that there is a considerable degree of common variation between projects and that factor analysis is considered both appropriate and likely to produce meaningful results. At the same time, Bartlett's sphericity test (testing the correlation matrix to determine whether the variables are uncorrelated) reinforces the appropriateness of factor analysis. The chi-square approximation is 10519.295, the degree of freedom is 435, and the significance level of the test is 0.000, decisively rejecting the null hypothesis of the identity matrix. This result confirms that there is a correlation between the variables, which is crucial for factor analysis. The statistical results help to establish the feasibility of the factor analysis of the dataset, confirm the effectiveness of the method, and enhance the reliability of the research results. High KMO measurements highlight important interrelationships between variables, indicating that factor analysis is well suited and ready to produce reliable results. In addition, the Bartlett test confirmed these findings, strengthening the methodological rigor of the study and improving the overall credibility of the study. This balance is crucial in providing a multifaceted view that minimizes bias and reinforces the applicability of the findings. The gender distribution was nearly equal, with 52.0% male participants and 48.0% female participants, providing insights into gender diversity in the study. Academic representation covers all four undergraduate years, ensuring that research covers a wide range of experiences. The distribution of family income is evenly distributed across all classes, reflecting a range of socioeconomic influences on students. Finally, the proportion of urban and rural backgrounds was 64.1% and 35.9%, respectively, highlighting the diversity of participants in terms of access to resources, exposure to opportunities and cultural background. Overall, this comprehensive demographic enhances the validity and generality of the research, ensuring that the findings are representative of a broad student population. Confirmatory factor Analysis (CFA) verifies potential variables associated with football tourism as a key validation process for the study structure. By examining factor loading, joint reliability (CR), and mean variance extraction (AVE), CFA assesses whether the observed variables adequately represent the expected underlying constructs. For the underlying variable "attitude towards employment policy", the factor load of the nine observed indicators ranged from 0.746 to 0.790, exceeding the threshold of 0.7. This indicates a strong correlation between the indicator and the underlying variable. The CR of 0.928 and the AVE of 0.587 further validate this structure, as both values exceed the recommended criteria, confirming that a large part of the variance of the indicator is explained by the underlying variable. Similarly, the "subjective norm" structure, as measured by seven indicators, shows a factor load ranging from 0.705 to 0.769, reflecting a strong association with underlying variables. The CR values of 0.892 and AVE values of 0.541 meet the threshold requirements, which proves the convergence validity of the construction. The seven indicators of the "employment capital" structure also present a favorable factor load between 0.723 and 0.778. CR was 0.902 and AVE was 0.569, which strengthened the validity of the construction. Finally, the "employment intentions" structure was assessed using seven indicators with a factor load range of 0.705 to 0.779. The CR and AVE of this structure are 0.899 and 0.561, which also meet the convergence validity criteria. These metrics are well aligned with their respective structures, as evidenced by high factor loads, satisfactory CR values, and AVE scores above the minimum threshold. This underpins the methodology of the study, ensuring that the underlying variables are reliable and valid for characterizing the investigated structure. A thorough verification process is fundamental to the credibility of the research and the accuracy of any subsequent analysis and conclusions drawn from the research. This study empirically tests the application of social capital and planned behavior theory to employment intention through structural equation model, and provides a rich theoretical basis for the two theories and extends them. The study reveals a significant positive relationship between employment policy attitudes (AE), subjective norms (SN), employment capital (EC), and employment intention (EI), and demonstrates the role of EC as a key link between individual attitudes and norms and employment intention, thus enriching social capital theory. In addition, the study supports the predictive power of planned behavior theory by observing direct effects in the context of employment intent, and extends it to the field of employment intent. The research also innovatively integrates social capital into the theoretical framework of planned behavior, providing a new perspective for understanding employment-related decisions. Indirect effect analysis further elucidates the interaction between social capital and planned behavior theory on employment intention, especially through the mediating role of employment capital, revealing how attitudes and subjective norms indirectly affect employment intention through social capital. This analysis of mediating mechanisms not only confirms existing theories, but also provides a significant contribution to the theoretical discussion through innovative applications of structural equation models, highlighting the 283 subtle mechanisms of how social capital and planning behavior work together to shape employment decisions. Research on college students' employment intentions reveals the significant impact of employment policy attitudes, subjective norms, employment capital and employment intentions, providing strategic insights for various stakeholders. Policymakers are advised to promote positive employment policies and norms, while educators should incorporate skills development into their curricula. Employers should recognize and promote labor capital, and individuals should actively develop their own labor capital. Although the study makes a valuable contribution, it also has limitations. It relies entirely on quantitative methods, focuses on a single demographic, and may not fully represent the diversity of the student body. Future studies should incorporate qualitative methods, expand the sample to include a broader and more diverse population, and consider regional differences. Addressing these constraints will enrich our understanding of the factors that influence employment intentions in different contexts. 5. Conclusion In this study, structural equation model was used to quantitatively analyze the relationship between employment policy attitudes (AE), subjective norms (SN), employment capital (EC) and employment intention (EI) of private university students in Guangdong Province. The study sample included 612 valid participants, and the results revealed significant direct effects of AE and SN on EC and EI. The path analysis verifies the hypothesis and shows that positive employment attitudes and social norms significantly affect the development of employment capital and the formation of employment intention. Mediation analysis further emphasizes the key role of EC in the relationship between AE and EI and SN and EI. The research provides empirical evidence for social capital theory and planned behavior theory, and expands the academic discussion of employment intent. The application of structural equation models contributes to a comprehensive understanding of how attitudes, social norms, and employment capital interact to shape employment intentions. In conclusion, the study provides valuable insights for understanding the dynamics of college students' employment decision-making, and emphasizes the importance of cultivating positive employment attitudes, strengthening social support norms and enhancing employment capital. These findings have practical implications for policymakers, educational institutions, employers and individuals, suggesting targeted strategies to improve employment outcomes. Future research should overcome the limitations of this study, such as methodology, demographic specificity, and geographic focus, to further enrich understanding in diverse contexts. References [1] Abbasi, G. A., Kumaravelu, J., Goh, Y.-N., & Singh, K. S. D. (2021). 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